For many years, Biology, in general, was a discipline considered to be similar to library sciences, due to the practice of collecting specimens and samples and cataloging them. (I made a herbarium for my high school project.) However, since the 1970s, the advancements in biologia molecular and in allied areas of biological research, has made Biology diversified. It is no longer a library science. Also, the need for interdisciplinary research has become more prominent. This is evident,specifically in Computational Biology and Bioinformática, with scientists from diverse background expertise, working on a common problem. In the current scenario, with the advent of newer technologies and techniques, interdisciplinary and integrative scientific research skills are in high demand.
Biologia Computacional e Bioinformática é uma das áreas, onde cientistas com diversos conhecimentos para dar resultados espetaculares. A citação seguinte resume de forma eloquente os benefícios da pesquisa interdisciplinar e integradora.
One of the most fascinating issues we’ve encountered is the notably different ways of thinking that typically characterize biologists and computer scientists. O biólogo reúne conhecimentos, muitas vezes descreve seu trabalho como se estivesse contando uma história, esforça-se para tirar conclusões e construir modelos, e aprecia que as exceções são tão comuns quanto as regras em nosso mundo biológico. Compare isto com a lógica e o processo orientado ao cientista da computação, para quem as regras e a otimização são os objetivos, e você tem o potencial de má comunicação. Os dois grupos, dado o mesmo problema, farão perguntas diferentes, pegarão detalhes diferentes, usarão metáforas diferentes para descrever o problema e chegarão à situação com pressupostos diferentes.
Por onde começar?
Em Biologia Computacional, algoritmos não destinados ou inventados para resolver problemas biológicos têm sido implementados com sucesso e as ferramentas desenvolvidas têm avançado imensamente no campo [3]. For example, dynamic programming, intended for finding the shortest path, was successfully applied for aligning sequences (both global and local alignment). An extension of the same is BLAST, a popular and essential tool for biologists to identify homologs for a given sequence. Thus, knowledge of algorithms and updating one with variants of the algorithms is essential for a computational biologist.
Com o advento de novas tecnologias e técnicas, as habilidades interdisciplinares e integrativas de pesquisa científica são muito requisitadas.
If you are a biologist, having the time tested routine laboratory work, would make you ask the question “I really don’t have time for this!”. And, you are right. But, think it in this way, the field of Computational Biology and Bioinformatics, was developed and nurtured by pioneers were physicists, biologists, chemists, statisticians, etc. Going out of the comfort zone, and listening to researchers from other areas over coffee or a drink is an excellent way to think out of the box. Conferences are a mine field, in this respect. Rather than listening to someone talking about their research (assuming that the research majorly overlaps your focused area, and most likely you have heard their talk on a different occasion), which will eventually be read by me in a few months; one can search for talks that have very less to do with your research. Such opportunities provide brainstorming ideas to implement techniques from other fields to your own research, more specifically Computational Biology and Bioinformatics.
If you don’t like meeting people, then following Twitter, research blogs, and joining discussion forums are the best alternatives.
Não é necessário se tornar um especialista em tudo. O objetivo é estar ciente de ferramentas, recursos e métodos que se destinam a outro propósito, mas que se modifica de acordo com suas necessidades. Por exemplo, os algoritmos genéticos (AG) são inspirados pelos eventos de recombinação que são observados na biologia. Assim, tornando as técnicas baseadas em AG mais otimizadas e bastante populares. Também é notável que os métodos de acoplamento molecular baseados em AG são igualmente populares em Biologia Computacional e Bioinformática, especificamente para a concepção de medicamentos.
The potential of using estatísticas, Matemática, computer science and signal processing in biology is immense. The key to develop an integrative research is communication. Communication with colleagues from other departments is the key. Also, a knack for looking out where the field is moving towards helps. Some interdisciplinary research in computational biology yielding groundbreaking results will be in discussed in subsequent posts.
A hora das ciências integrativas é agora!
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